Method for Detecting of Forest Degradation Method Using LandsatSatellite Images To Support MRV REDD in Halimun Salak National Park

ABSTRACT

Detection of degraded forest using remote sensing data has more technical challenges. For Monitoring Reporting and Verification (MRV) on REDD mechanism in regional scale, detection method of forest degradation is required. The objective of this research is to develop an approptiate method to detect forest degradation in forest conservation area of Halimun Salak National Park (HSNP). Forest Canopy Density (FCD), maximum likelihood, fuzzy and belief dempster shafer classification method were used to classify forest density and to detect forest degradation. Accuracy evaluation of classification and detection were based on overall accuracy which obtained from ground sample plot. Canopy density, LAI, crown indicator, stand density and basal area (lbds) were used as field indicators. Accuracy classification among stand density with four classification methods was FCD 61%, maximum likelihood 57%, fuzzy 51% and belief dempster shafer 49%. Based on evaluation of overall accuracy classification among canopy density and four classification method were FCD 86%, maximum likelihood 82%, fuzzy 73 % and belief dempster shafer 65%. Based on temporal detection accuracy from 2003 until 2008, FCD had overall accuracy 68 %. The result indicates that FCD is the best method to detect of forest degradation.

Keywords: Detection method, forest degradation, Landsat, MRV REDD

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Informasi Detil

Judul Seri

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No. Panggil

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Penerbit

: Colorado., 2012

Deskripsi Fisik

243-253

Bahasa

English

ISBN/ISSN

978-979-8452-45-1

Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subyek

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Info Detil Spesifik

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Pernyataan Tanggungjawab

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